NEWS
bambamR 0.1.0
- Standardize the named v5 package logo across README, documentation pages
and available application headers, with matching light and dark artwork.
New features
- Initial release of bambamR.
- Data import:
bb_read_fastq() and bb_read_bam() with ShortRead/Rsamtools
or base-R/system-samtools fallback.
- Quality control:
bb_qc(), bb_qc_summary(), and bb_plot_qc() for
per-read quality, GC content, and read-length distributions.
- Alignment:
bb_align() wrapping STAR, HISAT2, and minimap2.
- Read counting:
bb_count_reads() via GenomicAlignments or featureCounts.
- Normalization:
bb_normalize() supporting CPM, TPM (base R), TMM (edgeR),
and RLE (DESeq2).
- Differential expression:
bb_deseq2(), bb_edger(), and
bb_limma_voom() returning standardized result data.frames.
- Visualization:
bb_oncoplot(), bb_volcano(), bb_heatmap(),
bb_pca(), bb_ma_plot() — all return ggplot2 objects.
- Pipeline orchestrator:
bb_pipeline() runs the full analysis from FASTQ,
BAM, or count matrix to plots in a single call.
- Export:
bb_export_csv(), bb_export_tsv(), bb_export_rds().
- Shiny app:
bb_run_app() launches an interactive analysis dashboard.
- Example data:
bb_example_counts(), bb_example_mutations(), and
bb_example_de() provide bundled datasets for exploring all features.
- Two operating modes: minimal (CRAN-only) and full (+ Bioconductor).
All Bioconductor dependencies are optional and checked at runtime.
Bug fixes